Detecting anti-patterns in Java EE runtime system model

  • Authors:

  • Lei Zhang;Yanchun Sun;Hui Song;Weihu Wang;Gang Huang

  • Affiliations:

  • Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China

  • Venue:
  • Proceedings of the Fourth Asia-Pacific Symposium on Internetware
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

With the increasing complexity of enterprise applications, it becomes very challenging to create software systems which can exhibit a satisfactory performance behavior. In current system development practice, it often inevitably exists some "anti-patterns", which usually impede the performance or maintainability of software systems. Manually investigating anti-patterns in systems is a time-consuming and labor intensive task. To deal with this problem, we propose a general anti-pattern detection approach for Java EE application. Firstly, we propose a Java EE meta-model, based on which, we use QVT language to specify the detection process of anti-patterns. Secondly, we implement our approach on a runtime architecture-based reflective framework. When a Java EE application runs on one of the supported application servers, we can execute QVT script to detect whether or not there exists a specific anti-pattern in current system and get the report of potential problem components. At last, we perform a case study based on 35 well-known anti-patterns to evaluate the effectiveness and applicability of our approach.